Use of consensus clustering to identify distinct subtypes of chronic kidney disease and associated mortality risk
Yi Qin, Liping Xuan, Zhe Wu, Yujie Deng, Bin Liu, Shujie Wang · 2024
Read Use of consensus clustering to identify distinct subtypes of chronic kidney disease and associated mortality risk by Yi Qin, Liping Xuan, Zhe Wu, Yujie Deng, Bin Liu, Shujie Wang (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11611901.txt.
Description
Yi Qin and five co-authors sort chronic kidney disease into subtypes by letting the data group itself. Their study appeared in twenty twenty-four. Kidney disease has many causes and many outcomes, so one label may hide groups with very different risks.
The team used records from a large United States health survey, covering over six thousand people with the disease. A clustering method split them into four groups based on forty-five traits. One group was younger, with better heart and kidney markers. Another had the worst markers of all. Death risk rose step by step from the first group to the last. The split also held within groups that looked alike by kidney function alone.
Catalog record
| CREATOR | Yi Qin, Liping Xuan, Zhe Wu, Yujie Deng, Bin Liu, Shujie Wang |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 39 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |